# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import unittest

import numpy as np
from op_test import get_device_place, is_custom_device
from test_cuda_graph_static_mode import build_program, can_use_cuda_graph

import paddle
from paddle.base.dygraph.base import switch_to_static_graph
from paddle.device.cuda.graphs import CUDAGraph


@unittest.skipIf(
    not (paddle.is_compiled_with_cuda() or is_custom_device())
    or float(paddle.version.cuda()) < 11.0,
    "only support cuda >= 11.0",
)
class TestCUDAGraphInFirstBatch(unittest.TestCase):
    def setUp(self):
        if can_use_cuda_graph():
            paddle.set_flags(
                {
                    'FLAGS_allocator_strategy': 'auto_growth',
                    'FLAGS_sync_nccl_allreduce': False,
                    'FLAGS_cudnn_deterministic': True,
                    'FLAGS_use_stream_safe_cuda_allocator': True,
                }
            )

    @switch_to_static_graph
    def test_cuda_graph_in_first_batch(self):
        with paddle.pir_utils.OldIrGuard():
            if not can_use_cuda_graph():
                return

            startup = paddle.static.Program()
            main = paddle.static.Program()

            image, label, loss, lr = build_program(main, startup, 1, 10)

            place = get_device_place()
            exe = paddle.static.Executor(place)
            scope = paddle.static.Scope()
            with paddle.static.scope_guard(scope):
                exe.run(startup)
                build_strategy = paddle.static.BuildStrategy()
                build_strategy.allow_cuda_graph_capture = True
                compiled_program = paddle.static.CompiledProgram(
                    main, build_strategy=build_strategy
                )

                cuda_graph = None

                image_t = scope.var(image.name).get_tensor()
                label_t = scope.var(label.name).get_tensor()
                image_np = np.random.rand(1, 784).astype('float32')
                label_np = np.random.randint(
                    low=0, high=10, size=[1, 1], dtype='int64'
                )
                image_t.set(image_np, place)
                label_t.set(label_np, place)

                # CUDA Graph is not allowed to capture when running the first batch
                with self.assertRaises(RuntimeError):
                    cuda_graph = CUDAGraph(place, mode="global")
                    cuda_graph.capture_begin()
                    exe.run(compiled_program)
                    cuda_graph.capture_end()

                    if cuda_graph:
                        cuda_graph.reset()


if __name__ == "__main__":
    unittest.main()
